首页> 外国专利> UTILIZING MACHINE LEARNING AND A NETWORK OF TRUST FOR CROWD AND TRAFFIC CONTROL AND FOR MAPPING A GEOGRAPHICAL AREA

UTILIZING MACHINE LEARNING AND A NETWORK OF TRUST FOR CROWD AND TRAFFIC CONTROL AND FOR MAPPING A GEOGRAPHICAL AREA

机译:利用机器学习和人群和流量控制的信任网络,并用于映射地理区域

摘要

A device may receive application data associated with transaction applications of client devices and transaction card data associated with transaction cards. The device may receive geographical data identifying a geographical area associated with users of the client devices and the transaction cards. The device may determine, based on the application data, the transaction card data, and the geographical data, location data identifying geographical locations of the users in the geographical area. The device may determine, based on the location data, quantity data identifying quantities of the users located on multiple paths of the geographical area. The device may process the geographical data, the location data, and the quantity data, with a machine learning model, to identify a path with less than a threshold quantity of users in the geographical area. The device may perform one or more actions based on the path.
机译:设备可以接收与客户端设备的交易应用相关联的应用数据和与交易卡相关联的交易卡数据。 该设备可以接收标识与客户端设备和交易卡的用户相关联的地理区域的地理数据。 该设备可以基于应用数据,交易卡数据和地理数据来确定识别地理区域中用户的地理位置的位置数据。 该设备可以基于位置数据确定,该数量数据识别位于地理区域的多个路径上的用户的数量。 该设备可以利用机器学习模型处理地理数据,位置数据和数量数据,以识别具有小于地理区域中用户的阈值量的路径。 该设备可以基于路径执行一个或多个动作。

著录项

  • 公开/公告号US2022034664A1

    专利类型

  • 公开/公告日2022-02-03

    原文格式PDF

  • 申请/专利权人 CAPITAL ONE SERVICES LLC;

    申请/专利号US202016947474

  • 发明设计人 ADAM VUKICH;GEORGE BERGERON;JAMES ZARAKAS;

    申请日2020-08-03

  • 分类号G01C21/34;G06K9;G06K9/62;G01C21/26;

  • 国家 US

  • 入库时间 2022-08-24 23:36:41

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